idea-discovery skill

Override for Codex users who want Gemini, not a second Codex agent, to act as the reviewer. Install this package after skills/skills-codex/*.

Workflow 1: Idea Discovery Pipeline

Gemini overlay assurance: reviewindependence: cross-family and acceptancestatus: accepted.

Orchestrate a complete idea discovery workflow for: $ARGUMENTS

Overview

This skill chains sub-skills into a single automated pipeline:

/research-lit → /idea-creator → /novelty-check → /research-review → /research-refine-pipeline
  (survey)      (brainstorm)    (verify novel)    (critical feedback)  (refine method + plan experiments)

Each phase builds on the previous one's output. The final deliverables are a validated idea-stage/IDEAREPORT.md with ranked ideas, plus a refined proposal (refine-logs/FINALPROPOSAL.md) and experiment plan (refine-logs/EXPERIMENT_PLAN.md) for the top idea.

Constants

• PILOTMAXHOURS = 2 — Skip any pilot experiment estimated to take > 2 hours per GPU. Flag as "needs manual pilot" in the report.
• PILOTTIMEOUTHOURS = 3 — Hard timeout: kill any running pilot that exceeds 3 hours. Collect partial results if available.
• MAXPILOTIDEAS = 3 — Run pilots for at most 3 top ideas in parallel. Additional ideas are validated on paper only.
• MAXTOTALGPUHOURS = 8** — Total GPU budget across all pilots. If exceeded, skip remaining pilots and note in report.
• AUTOPROCEED = true** — When true, checkpoints are informational: report the selected option and continue in the same turn. Set to false to ask for explicit user confirmation and end the turn at each selection checkpoint.
• OUTPUTDIR = idea-stage/** — All idea-stage outputs go here. Create the directory if it doesn't exist.
• REVIEWERMODEL = gemini-review** — Gemini reviewer invoked through the local gemini-review MCP bridge. Passed to the reviewer-aware sub-skills installed by this overlay.
• ARXIVDOWNLOAD = false** — When true, /research-lit downloads the top relevant arXiv PDFs during Phase 1. When false (default), only fetches metadata. Passed through to /research-lit.

💡 These are defaults. Override by telling the skill, e.g., /idea-discovery "topic" — pilot budget: 4h per idea, 20h total or /idea-discovery "topic" — arxiv download: true.

Checkpoint execution rule

Resolve AUTO_PROCEED once from $ARGUMENTS before Phase 1 and keep that mode for the entire workflow.

not a question. State the result and the automatically selected next action, then continue executing in the same turn. Do not ask for confirmation, request user input, sleep, wait for silence, or end the turn at a checkpoint.

• AUTOPROCEED=true is non-blocking.** A checkpoint is a progress update,

end the turn. Resume only after an explicit reply.

• AUTOPROCEED=false is blocking.** Present the options, ask the user, and

Never implement auto-proceed as “ask, then continue if there is no response.” Once a turn ends, silence cannot resume the workflow. The user can still interrupt a non-blocking run at any time.

This rule governs only AUTOPROCEED-controlled selection checkpoints. If the user explicitly enables a Feishu interactive gate, that external approval or reply is an intentional blocking exception; wait for that user-controlled gate rather than treating it as a silence timeout. Feishu off/push-only modes remain non-blocking under AUTOPROCEED=true.

Pipeline

Phase 1: Literature Survey

Invoke /research-lit to map the research landscape:

/research-lit "$ARGUMENTS"

What this does:

• Search arXiv, Google Scholar, Semantic Scholar for recent papers
• Build a landscape map: sub-directions, approaches, open problems
• Identify structural gaps and recurring limitations
• Output a literature summary (saved to working notes)

🚦 Checkpoint: Present the landscape summary to the user.

When AUTOPROCEED=true (non-blocking):** report the selected direction and continue immediately in the same turn, without a question:

📚 Literature survey complete. Here's what I found:
- [key findings, gaps, open problems]

AUTO_PROCEED: selected [top-ranked direction]. Continuing to Phase 2.

When AUTOPROCEED=false (blocking):** present the same findings, ask Does this match your understanding? Should I adjust the scope before generating ideas?, then end the turn.

• User approves → proceed to Phase 2 with the best direction.
• User requests changes (e.g., "focus more on X", "ignore Y", "too broad") → refine the search with updated queries, re-run /research-lit with adjusted scope, and present again. Repeat until the user is satisfied.

Phase 2: Idea Generation + Filtering + Pilots

Invoke /idea-creator with the landscape context:

/idea-creator "$ARGUMENTS"

What this does:

• Brainstorm 8-12 concrete ideas via the Gemini-backed /idea-creator overlay
• Filter by feasibility, compute cost, quick novelty search
• Deep validate top ideas (full novelty check + devil's advocate)
• Run parallel pilot experiments on available GPUs (top 2-3 ideas)
• Rank by empirical signal
• Output idea-stage/IDEA_REPORT.md

🚦 Checkpoint: Present idea-stage/IDEA_REPORT.md ranked ideas to the user.

When AUTOPROCEED=true (non-blocking):** report the automatic selection and continue immediately in the same turn, without a question:

💡 Generated X ideas, filtered to Y, piloted Z. Top results:

1. [Idea 1] — Pilot: POSITIVE (+X%)
2. [Idea 2] — Pilot: WEAK POSITIVE (+Y%)
3. [Idea 3] — Pilot: NEGATIVE, eliminated

AUTO_PROCEED: selected [top-ranked idea(s)]. Continuing to Phase 3.

When AUTOPROCEED=false (blocking):** present the same ranking, ask Which ideas should I validate further? Or should I regenerate with different constraints?, then end the turn.

• User picks ideas → proceed to Phase 3 with the selected ideas.
• User unhappy with all ideas → collect feedback ("what's missing?", "what direction do you prefer?"), update the prompt with user's constraints, and re-run Phase 2 (idea generation). Repeat until the user selects at least 1 idea.
• User wants to adjust scope → go back to Phase 1 with refined direction.

Phase 3: Deep Novelty Verification

For each top idea (positive pilot signal), run a thorough novelty check:

/novelty-check "[top idea 1 description]"
/novelty-check "[top idea 2 description]"

What this does:

• Multi-source literature search (arXiv, Scholar, Semantic Scholar)
• Cross-verify with the Gemini-backed /novelty-check overlay
• Check for concurrent work (last 3-6 months)
• Identify closest existing work and differentiation points

Update idea-stage/IDEAREPORT.md** with deep novelty results. Eliminate any idea that turns out to be already published.

Phase 4: External Critical Review

For the surviving top idea(s), get a sharp outside read — strongest case, named risks, and the cheapest discriminating next experiment; the core hypothesis is not up for rewriting:

/research-review "[top idea with hypothesis + pilot results]"

What this does:

• Gemini acts as a senior reviewer (NeurIPS/ICML level) via the local gemini-review MCP bridge
• Scores the idea, identifies weaknesses, suggests minimum viable improvements
• Provides concrete feedback on experimental design

Update idea-stage/IDEAREPORT.md** with reviewer feedback and revised plan.

Phase 4.5: Method Refinement + Experiment Planning

After review, refine the top idea into a concrete proposal and plan experiments:

/research-refine-pipeline "[top idea description + pilot results + reviewer feedback]"

What this does:

• Freeze a Problem Anchor to prevent scope drift
• Refine the method via Gemini review — reviewer risks choose the next tests, they do not add components; the score is advisory, and preserving the core hypothesis outranks pleasing the reviewer
• Generate a claim-driven experiment roadmap with ablations, budgets, and run order
• Output: refine-logs/FINALPROPOSAL.md, refine-logs/EXPERIMENTPLAN.md, refine-logs/EXPERIMENT_TRACKER.md

🚦 Checkpoint: Present the refined proposal summary.

When AUTOPROCEED=true (non-blocking):** report that the proposal was selected and continue immediately in the same turn, without a question:

🔬 Method refined and experiment plan ready:
- Problem anchor: [anchored problem]
- Method thesis: [one sentence]
- Dominant contribution: [what's new]
- Must-run experiments: [N blocks]
- First 3 runs to launch: [list]

AUTO_PROCEED: accepted the top proposal. Continuing to Final Report.